Abstract

Arc welding can be used to weld the components of rail car brackets during assembly operation. In this study, the welding parameters, namely voltage, current, speed, and arc length, were optimized using the Taguchi method and response surface methodology (RSM). A predictive model was thereafter obtained that correlates the weld distortion and hardness as a function of the welding parameters. The experimental design which consists of Taguchi orthogonal array of L9, three level-four factor matrix was used as input parameters to determine the weld distortion and hardness while the RSM was used to study the cross effect (interaction) of various process parameters on the weld distortion. Analysis of variance (ANOVA) was used to further test and validate the developed model for adequacy and the regression model was found to be highly significant at 95% confidence level as correlation coefficients were very close to 1. The results obtained also show high degree of convergence of the welded components with changes in welding parameters indicating that weld distortion is kept within the permissible range. This will reduce the production cost and increase the quality as well as the reliability of weld during welding processes.